A New Model to Predict the Oxidation Kinetics of Zirconium Alloys in a Pressurized Water Reactor
Bibliographic record
Abstract
The previous CEA corrosion code COCHISE provided satisfactory simulations of in-reactor corrosion of the fuel cladding when used in its validity range. In contrast, it could lead to hazardous predictions if applied out of this range due to the strongly linked parameters mainly based on the analysis of French pressurized water reactor (PWR) data. To predict the oxidation kinetics for new operating conditions or new materials, the CEA and EDF decided to develop a new model, named CORCY, which is based on a more phenomenological approach and uses separate parameters deduced from analytical experiments. The aim of this paper is to present the new model for Zircaloy-4 in PWR. The phenomenological approach is described. It is based on out- and in-pile data. Typically, since (1) the oxidation kinetics of zirconium alloys in autoclave are periodic, and (2) the oxide films formed in autoclave, in out-of-pile loop, and in-reactor all exhibit periodic lateral cracks with a period similar to the oxide thickness to transition, the oxidation kinetics in CORCY are characterized by a cyclic repetition of semi-parabolic law. Each model parameter is detailed. They are deduced separately from (a) oxidation tests performed in autoclave on fresh alloys to determine their kinetics; (b) oxidation tests performed in the out-of-pile corrosion loops Corail and Reggae to quantify the effects of thermo-hydraulic conditions; (c) data provided by Testing Material Reactors (OSIRIS and Halden reactor) during isothermal oxidation to determine the effects of irradiation; and (d) oxidation tests performed on pre-hydrided alloys to take into account the accelerated corrosion phase occurring, in reactor, for Zircaloy-4 at high burn-up. After describing both the phenomenological approach and the different model parameters, a comparison of measured and calculated corrosion data from French PWRs at a burn-up up to 65 GWd/tU is provided.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".